{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Node classification with Node2Vec\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "source": [
    "<table><tr><td>Run the latest release of this notebook:</td><td><a href=\"https://mybinder.org/v2/gh/stellargraph/stellargraph/master?urlpath=lab/tree/demos/node-classification/node2vec-node-classification.ipynb\" alt=\"Open In Binder\" target=\"_parent\"><img src=\"https://mybinder.org/badge_logo.svg\"/></a></td><td><a href=\"https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/node-classification/node2vec-node-classification.ipynb\" alt=\"Open In Colab\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a></td></tr></table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "An example of node classification on a homogeneous graph using the `Node2Vec` representation learning algorithm. The example uses components from the `stellargraph`, `Gensim`, and `scikit-learn` libraries.\n",
    "\n",
    "**Note:** For clarity of exposition, this notebook forgoes the use of standard machine learning practices such as `Node2Vec` parameter tuning, node feature standarization, data splitting that handles class imbalance, classifier selection, and classifier tuning to maximize predictive accuracy. We leave such improvements to the reader.\n",
    "\n",
    "### References\n",
    "\n",
    "[1] Node2Vec: Scalable Feature Learning for Networks. A. Grover, J. Leskovec. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. ([link](https://snap.stanford.edu/node2vec/))\n",
    "\n",
    "[2] Distributed representations of words and phrases and their compositionality. T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean.  In Advances in Neural Information Processing Systems (NIPS), pp. 3111-3119, 2013. ([link](https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf))\n",
    "\n",
    "[3] Gensim: Topic modelling for humans. ([link](https://radimrehurek.com/gensim/))\n",
    "\n",
    "[4] scikit-learn: Machine Learning in Python ([link](http://scikit-learn.org/stable/))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "outputs": [],
   "source": [
    "# install StellarGraph if running on Google Colab\n",
    "import sys\n",
    "if 'google.colab' in sys.modules:\n",
    "  %pip install -q stellargraph[demos]==1.2.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "VersionCheck"
    ]
   },
   "outputs": [],
   "source": [
    "# verify that we're using the correct version of StellarGraph for this notebook\n",
    "import stellargraph as sg\n",
    "\n",
    "try:\n",
    "    sg.utils.validate_notebook_version(\"1.2.1\")\n",
    "except AttributeError:\n",
    "    raise ValueError(\n",
    "        f\"This notebook requires StellarGraph version 1.2.1, but a different version {sg.__version__} is installed.  Please see <https://github.com/stellargraph/stellargraph/issues/1172>.\"\n",
    "    ) from None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegressionCV\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "import os\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from stellargraph.data import BiasedRandomWalk\n",
    "from stellargraph import StellarGraph\n",
    "from stellargraph import datasets\n",
    "from IPython.display import display, HTML\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset\n",
    "\n",
    "For clarity, we use only the largest connected component, ignoring isolated nodes and subgraphs; having these in the data does not prevent the algorithm from running and producing valid results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "DataLoadingLinks"
    ]
   },
   "source": [
    "(See [the \"Loading from Pandas\" demo](../basics/loading-pandas.ipynb) for details on how data can be loaded.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "DataLoading"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary. The dictionary consists of 1433 unique words."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = datasets.Cora()\n",
    "display(HTML(dataset.description))\n",
    "G, node_subjects = dataset.load(largest_connected_component_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "StellarGraph: Undirected multigraph\n",
      " Nodes: 2485, Edges: 5209\n",
      "\n",
      " Node types:\n",
      "  paper: [2485]\n",
      "    Edge types: paper-cites->paper\n",
      "\n",
      " Edge types:\n",
      "    paper-cites->paper: [5209]\n"
     ]
    }
   ],
   "source": [
    "print(G.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Node2Vec algorithm\n",
    "\n",
    "The Node2Vec algorithm introduced in [1] is a 2-step representation learning algorithm. The two steps are,\n",
    "\n",
    "1. Use second-order random walks to generate sentences from a graph. A sentence is a list of node ids. The set of all sentences makes a corpus.\n",
    "\n",
    "2. The corpus is then used to learn an embedding vector for each node in the graph. Each node id is considered a unique word/token in a dictionary that has size equal to the number of nodes in the graph. The Word2Vec algorithm [2], is used for calculating the embedding vectors.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Corpus generation using random walks\n",
    "\n",
    "The stellargraph library provides an implementation for second-order random walks as required by Node2Vec. The random walks have fixed maximum length and are controlled by two parameters `p` and `q`. See [1] for a detailed description of these parameters. \n",
    "\n",
    "We are going to start 10 random walks from each node in the graph with a length up to 100. We set parameter `p` to 0.5 and `q` to 2.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of random walks: 24850\n"
     ]
    }
   ],
   "source": [
    "rw = BiasedRandomWalk(G)\n",
    "\n",
    "walks = rw.run(\n",
    "    nodes=list(G.nodes()),  # root nodes\n",
    "    length=100,  # maximum length of a random walk\n",
    "    n=10,  # number of random walks per root node\n",
    "    p=0.5,  # Defines (unormalised) probability, 1/p, of returning to source node\n",
    "    q=2.0,  # Defines (unormalised) probability, 1/q, for moving away from source node\n",
    ")\n",
    "print(\"Number of random walks: {}\".format(len(walks)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Representation Learning using Word2Vec\n",
    "\n",
    "We use the `Word2Vec` [2], implementation in the free Python library `Gensim` [3], to learn representations for each node in the graph. It works with `str` tokens, but the graph has integer IDs, so they're converted to `str` here.\n",
    "\n",
    "We set the dimensionality of the learned embedding vectors to 128 as in [1]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gensim.models import Word2Vec\n",
    "\n",
    "str_walks = [[str(n) for n in walk] for walk in walks]\n",
    "model = Word2Vec(str_walks, size=128, window=5, min_count=0, sg=1, workers=2, iter=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128,)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The embedding vectors can be retrieved from model.wv using the node ID as key.\n",
    "model.wv[\"19231\"].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualise Node Embeddings\n",
    "\n",
    "We retrieve the `Word2Vec` node embeddings that are 128-dimensional vectors and then we project them down to 2 dimensions using the [t-SNE](http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html) algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Retrieve node embeddings and corresponding subjects\n",
    "node_ids = model.wv.index2word  # list of node IDs\n",
    "node_embeddings = (\n",
    "    model.wv.vectors\n",
    ")  # numpy.ndarray of size number of nodes times embeddings dimensionality\n",
    "node_targets = node_subjects[[int(node_id) for node_id in node_ids]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply t-SNE transformation on node embeddings\n",
    "tsne = TSNE(n_components=2)\n",
    "node_embeddings_2d = tsne.fit_transform(node_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x15b689710>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# draw the points\n",
    "alpha = 0.7\n",
    "label_map = {l: i for i, l in enumerate(np.unique(node_targets))}\n",
    "node_colours = [label_map[target] for target in node_targets]\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.scatter(\n",
    "    node_embeddings_2d[:, 0],\n",
    "    node_embeddings_2d[:, 1],\n",
    "    c=node_colours,\n",
    "    cmap=\"jet\",\n",
    "    alpha=alpha,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downstream task\n",
    "\n",
    "The node embeddings calculated using `Word2Vec` can be used as feature vectors in a downstream task such as node attribute inference. \n",
    "\n",
    "In this example, we will use the `Node2Vec` node embeddings to train a classifier to predict the subject of a paper in Cora."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# X will hold the 128-dimensional input features\n",
    "X = node_embeddings\n",
    "# y holds the corresponding target values\n",
    "y = np.array(node_targets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Splitting\n",
    "\n",
    "We split the data into train and test sets. \n",
    "\n",
    "We use 75% of the data for training and the remaining 25% for testing as a hold out test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.1, test_size=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Array shapes:\n",
      " X_train = (248, 128)\n",
      " y_train = (248,)\n",
      " X_test = (2237, 128)\n",
      " y_test = (2237,)\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Array shapes:\\n X_train = {}\\n y_train = {}\\n X_test = {}\\n y_test = {}\".format(\n",
    "        X_train.shape, y_train.shape, X_test.shape, y_test.shape\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Classifier Training\n",
    "\n",
    "We train a Logistic Regression classifier on the training data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegressionCV(Cs=10, class_weight=None, cv=10, dual=False,\n",
       "                     fit_intercept=True, intercept_scaling=1.0, l1_ratios=None,\n",
       "                     max_iter=300, multi_class='ovr', n_jobs=None, penalty='l2',\n",
       "                     random_state=None, refit=True, scoring='accuracy',\n",
       "                     solver='lbfgs', tol=0.0001, verbose=False)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = LogisticRegressionCV(\n",
    "    Cs=10, cv=10, scoring=\"accuracy\", verbose=False, multi_class=\"ovr\", max_iter=300\n",
    ")\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predict the hold out test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the accuracy of the classifier on the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7223960661600357"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "source": [
    "<table><tr><td>Run the latest release of this notebook:</td><td><a href=\"https://mybinder.org/v2/gh/stellargraph/stellargraph/master?urlpath=lab/tree/demos/node-classification/node2vec-node-classification.ipynb\" alt=\"Open In Binder\" target=\"_parent\"><img src=\"https://mybinder.org/badge_logo.svg\"/></a></td><td><a href=\"https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/node-classification/node2vec-node-classification.ipynb\" alt=\"Open In Colab\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a></td></tr></table>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
